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用于在临床文档中表示不良敏感性信息的标准信息模型。

Standard Information Models for Representing Adverse Sensitivity Information in Clinical Documents.

作者信息

Topaz M, Seger D L, Goss F, Lai K, Slight S P, Lau J J, Nandigam H, Zhou L

机构信息

Maxim Topaz PhD, RN, MA, 93 Worcester St., Wellesley Gateway, Suite 2030I, Wellesley, MA, 02481, USA, E mail:

出版信息

Methods Inf Med. 2016;55(2):151-7. doi: 10.3414/ME15-01-0081. Epub 2016 Feb 24.

Abstract

BACKGROUND

Adverse sensitivity (e.g., allergy and intolerance) information is a critical component of any electronic health record system. While several standards exist for structured entry of adverse sensitivity information, many clinicians record this data as free text.

OBJECTIVES

This study aimed to 1) identify and compare the existing common adverse sensitivity information models, and 2) to evaluate the coverage of the adverse sensitivity information models for representing allergy information on a subset of inpatient and outpatient adverse sensitivity clinical notes.

METHODS

We compared four common adverse sensitivity information models: Health Level 7 Allergy and Intolerance Domain Analysis Model, HL7-DAM; the Fast Healthcare Interoperability Resources, FHIR; the Consolidated Continuity of Care Document, C-CDA; and OpenEHR, and evaluated their coverage on a corpus of inpatient and outpatient notes (n = 120).

RESULTS

We found that allergy specialists' notes had the highest frequency of adverse sensitivity attributes per note, whereas emergency department notes had the fewest attributes. Overall, the models had many similarities in the central attributes which covered between 75% and 95% of adverse sensitivity information contained within the notes. However, representations of some attributes (especially the value-sets) were not well aligned between the models, which is likely to present an obstacle for achieving data interoperability. Also, adverse sensitivity exceptions were not well represented among the information models.

CONCLUSIONS

Although we found that common adverse sensitivity models cover a significant portion of relevant information in the clinical notes, our results highlight areas needed to be reconciled between the standards for data interoperability.

摘要

背景

不良敏感性(如过敏和不耐受)信息是任何电子健康记录系统的关键组成部分。虽然存在一些用于结构化录入不良敏感性信息的标准,但许多临床医生将此数据记录为自由文本。

目的

本研究旨在1)识别和比较现有的常见不良敏感性信息模型,以及2)评估不良敏感性信息模型在住院和门诊不良敏感性临床记录子集中表示过敏信息的覆盖范围。

方法

我们比较了四种常见的不良敏感性信息模型:健康等级7过敏和不耐受领域分析模型(HL7-DAM)、快速医疗保健互操作性资源(FHIR)、连续护理文档(C-CDA)和开放电子健康记录(OpenEHR),并评估了它们在住院和门诊记录语料库(n = 120)上的覆盖范围。

结果

我们发现过敏专科医生的记录中每条记录的不良敏感性属性频率最高,而急诊科记录的属性最少。总体而言,这些模型在核心属性方面有许多相似之处,这些核心属性涵盖了记录中75%至95%的不良敏感性信息。然而,模型之间某些属性(尤其是值集)的表示并不一致,这可能会成为实现数据互操作性的障碍。此外,不良敏感性异常情况在信息模型中没有得到很好的体现。

结论

虽然我们发现常见的不良敏感性模型涵盖了临床记录中很大一部分相关信息,但我们的结果突出了数据互操作性标准之间需要协调的领域。

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